Overview

Dataset statistics

Number of variables4
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory996.0 B
Average record size in memory41.5 B

Variable types

Numeric4

Dataset

Description본 데이터는 KOGAS 고압 배관망을 통해 공급되는 천연가스 내 수소를 일정 부피 비율로 혼입할 시 감축되는 천연가스 량, 수소 필요량, 온실가스 배출감축량을 계산한 표임. ※가정: 4,000만 톤 천연가스 대상 수소혼입 ※참고값: - 천연가스 중량단위 열량: 54.686 MJ/kg, 수소 중량단위 열량: 141.95 MJ/kg - 천연가스 부피단위 열량: 42.704 MJ/Nm3, 수소 부피단위 열량: 12.77 Nm3/h - 천연가스 기체 밀도: 0.7809 kg/Nm3, 수소기체 밀도: 0.08988 kg/Nm3 ※ 온실가스 배출량 계산 (한국에너지공단 홈페이지 참조: 홈 -> 기후변화대응 -> 배출량 자동계산) - 천연가스 1톤당 1,281.00 Nm3 - 천연가스 순발열량: 38.50 MJ/Nm3 - 천연가스 탄소배출계수 : 15.236 tC/TJ - CO2 환산수치 : 55.87 tCO2/TJ
URLhttps://www.data.go.kr/data/15118624/fileData.do

Alerts

수소혼입농도 (부피_퍼센트) is highly overall correlated with 천연가스 사용량 (톤_연간 기준) and 2 other fieldsHigh correlation
천연가스 사용량 (톤_연간 기준) is highly overall correlated with 수소혼입농도 (부피_퍼센트) and 2 other fieldsHigh correlation
수소 필요량 (톤_연간 기준) is highly overall correlated with 수소혼입농도 (부피_퍼센트) and 2 other fieldsHigh correlation
온실가스 배출감축량 (톤_연간 기준) is highly overall correlated with 수소혼입농도 (부피_퍼센트) and 2 other fieldsHigh correlation
수소혼입농도 (부피_퍼센트) has unique valuesUnique
천연가스 사용량 (톤_연간 기준) has unique valuesUnique
수소 필요량 (톤_연간 기준) has unique valuesUnique
온실가스 배출감축량 (톤_연간 기준) has unique valuesUnique
수소혼입농도 (부피_퍼센트) has 1 (4.2%) zerosZeros
천연가스 사용량 (톤_연간 기준) has 1 (4.2%) zerosZeros
수소 필요량 (톤_연간 기준) has 1 (4.2%) zerosZeros
온실가스 배출감축량 (톤_연간 기준) has 1 (4.2%) zerosZeros

Reproduction

Analysis started2023-12-12 11:20:13.851595
Analysis finished2023-12-12 11:20:18.554415
Duration4.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

수소혼입농도 (부피_퍼센트)
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.791667
Minimum0
Maximum100
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T20:20:18.646062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.15
Q15.75
median17.5
Q346.25
95-th percentile88.5
Maximum100
Range100
Interquartile range (IQR)40.5

Descriptive statistics

Standard deviation30.633853
Coefficient of variation (CV)1.0282692
Kurtosis-0.095078503
Mean29.791667
Median Absolute Deviation (MAD)15
Skewness1.0169367
Sum715
Variance938.43297
MonotonicityStrictly increasing
2023-12-12T20:20:18.836794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 1
 
4.2%
25 1
 
4.2%
100 1
 
4.2%
90 1
 
4.2%
80 1
 
4.2%
70 1
 
4.2%
60 1
 
4.2%
50 1
 
4.2%
45 1
 
4.2%
40 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
0 1
4.2%
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
9 1
4.2%
ValueCountFrequency (%)
100 1
4.2%
90 1
4.2%
80 1
4.2%
70 1
4.2%
60 1
4.2%
50 1
4.2%
45 1
4.2%
40 1
4.2%
35 1
4.2%
30 1
4.2%

천연가스 사용량 (톤_연간 기준)
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32962425
Minimum0
Maximum40000000
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T20:20:19.039066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11944797
Q131802418
median37606840
Q339283322
95-th percentile39861249
Maximum40000000
Range40000000
Interquartile range (IQR)7480904

Descriptive statistics

Standard deviation10285188
Coefficient of variation (CV)0.31202766
Kurtosis4.1145441
Mean32962425
Median Absolute Deviation (MAD)2150226.5
Skewness-2.0772975
Sum7.910982 × 108
Variance1.057851 × 1014
MonotonicityStrictly decreasing
2023-12-12T20:20:19.683284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
40000000 1
 
4.2%
36375045 1
 
4.2%
0 1
 
4.2%
10838097 1
 
4.2%
18216099 1
 
4.2%
23562886 1
 
4.2%
27615776 1
 
4.2%
30793748 1
 
4.2%
32138641 1
 
4.2%
33352512 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
0 1
4.2%
10838097 1
4.2%
18216099 1
4.2%
23562886 1
4.2%
27615776 1
4.2%
30793748 1
4.2%
32138641 1
4.2%
33352512 1
4.2%
34453617 1
4.2%
35456974 1
4.2%
ValueCountFrequency (%)
40000000 1
4.2%
39879570 1
4.2%
39757427 1
4.2%
39633535 1
4.2%
39507856 1
4.2%
39380350 1
4.2%
39250979 1
4.2%
39119700 1
4.2%
38986471 1
4.2%
38851248 1
4.2%

수소 필요량 (톤_연간 기준)
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2709382.9
Minimum0
Maximum15399525
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T20:20:19.876041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile53417.6
Q1275912.5
median921338.5
Q33155972
95-th percentile10800920
Maximum15399525
Range15399525
Interquartile range (IQR)2880059.5

Descriptive statistics

Standard deviation3959675.3
Coefficient of variation (CV)1.4614676
Kurtosis4.1145443
Mean2709382.9
Median Absolute Deviation (MAD)827811.5
Skewness2.0772975
Sum65025190
Variance1.5679029 × 1013
MonotonicityStrictly increasing
2023-12-12T20:20:20.094031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 1
 
4.2%
1395565 1
 
4.2%
15399525 1
 
4.2%
11226986 1
 
4.2%
8386543 1
 
4.2%
6328094 1
 
4.2%
4767779 1
 
4.2%
3544298 1
 
4.2%
3026530 1
 
4.2%
2559204 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
0 1
4.2%
46364 1
4.2%
93388 1
4.2%
141085 1
4.2%
189470 1
4.2%
238558 1
4.2%
288364 1
4.2%
338905 1
4.2%
390197 1
4.2%
442256 1
4.2%
ValueCountFrequency (%)
15399525 1
4.2%
11226986 1
4.2%
8386543 1
4.2%
6328094 1
4.2%
4767779 1
4.2%
3544298 1
4.2%
3026530 1
4.2%
2559204 1
4.2%
2135291 1
4.2%
1749011 1
4.2%

온실가스 배출감축량 (톤_연간 기준)
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19389888
Minimum0
Maximum1.1020778 × 108
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T20:20:20.337375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile382288.05
Q11974588.2
median6593623
Q322585933
95-th percentile77297538
Maximum1.1020778 × 108
Range1.1020778 × 108
Interquartile range (IQR)20611345

Descriptive statistics

Standard deviation28337694
Coefficient of variation (CV)1.4614676
Kurtosis4.1145442
Mean19389888
Median Absolute Deviation (MAD)5924291.5
Skewness2.0772975
Sum4.6535732 × 108
Variance8.0302488 × 1014
MonotonicityStrictly increasing
2023-12-12T20:20:20.568089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 1
 
4.2%
9987455 1
 
4.2%
110207778 1
 
4.2%
80346712 1
 
4.2%
60018884 1
 
4.2%
45287445 1
 
4.2%
34120946 1
 
4.2%
25365014 1
 
4.2%
21659573 1
 
4.2%
18315123 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
0 1
4.2%
331809 1
4.2%
668336 1
4.2%
1009683 1
4.2%
1355953 1
4.2%
1707256 1
4.2%
2063699 1
4.2%
2425399 1
4.2%
2792471 1
4.2%
3165036 1
4.2%
ValueCountFrequency (%)
110207778 1
4.2%
80346712 1
4.2%
60018884 1
4.2%
45287445 1
4.2%
34120946 1
4.2%
25365014 1
4.2%
21659573 1
4.2%
18315123 1
4.2%
15281362 1
4.2%
12516919 1
4.2%

Interactions

2023-12-12T20:20:17.785178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:20:15.759871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:20:16.541788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:20:17.215558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:20:17.909223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:20:15.969413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:20:16.725083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:20:17.354188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:20:18.047246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:20:16.182835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:20:16.892218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:20:17.509939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:20:18.183432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:20:16.380037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:20:17.067442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:20:17.652059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:20:20.751438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수소혼입농도 (부피_퍼센트)천연가스 사용량 (톤_연간 기준)수소 필요량 (톤_연간 기준)온실가스 배출감축량 (톤_연간 기준)
수소혼입농도 (부피_퍼센트)1.0000.9770.9770.977
천연가스 사용량 (톤_연간 기준)0.9771.0001.0001.000
수소 필요량 (톤_연간 기준)0.9771.0001.0001.000
온실가스 배출감축량 (톤_연간 기준)0.9771.0001.0001.000
2023-12-12T20:20:20.962471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수소혼입농도 (부피_퍼센트)천연가스 사용량 (톤_연간 기준)수소 필요량 (톤_연간 기준)온실가스 배출감축량 (톤_연간 기준)
수소혼입농도 (부피_퍼센트)1.000-1.0001.0001.000
천연가스 사용량 (톤_연간 기준)-1.0001.000-1.000-1.000
수소 필요량 (톤_연간 기준)1.000-1.0001.0001.000
온실가스 배출감축량 (톤_연간 기준)1.000-1.0001.0001.000

Missing values

2023-12-12T20:20:18.347003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:20:18.484439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

수소혼입농도 (부피_퍼센트)천연가스 사용량 (톤_연간 기준)수소 필요량 (톤_연간 기준)온실가스 배출감축량 (톤_연간 기준)
004000000000
113987957046364331809
223975742793388668336
33396335351410851009683
44395078561894701355953
55393803502385581707256
66392509792883642063699
77391197003389052425399
88389864713901972792471
99388512484422563165036
수소혼입농도 (부피_퍼센트)천연가스 사용량 (톤_연간 기준)수소 필요량 (톤_연간 기준)온실가스 배출감축량 (톤_연간 기준)
143035456974174901112516919
153534453617213529115281362
164033352512255920418315123
174532138641302653021659573
185030793748354429825365014
196027615776476777934120946
207023562886632809445287445
218018216099838654360018884
2290108380971122698680346712
23100015399525110207778